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Revision 64a4bbd5

Added by Benoit Parmentier about 8 years ago

adding input arguments, data_type, scaling and more

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climate/research/oregon/interpolation/global_product_assessment_part0.R
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#
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#AUTHOR: Benoit Parmentier
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#CREATED ON: 10/27/2016
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#MODIFIED ON: 11/27/2016
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#MODIFIED ON: 11/28/2016
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#Version: 1
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#PROJECT: Environmental Layers project
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#COMMENTS:
......
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source(file.path(script_path,function_assessment_part3)) #source all functions used in this script
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#Product assessment


  		




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function_product_assessment_part0_functions <- "global_product_assessment_part0_functions_11272016.R"


  		




  
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function_product_assessment_part0_functions <- "global_product_assessment_part0_functions_11292016b.R"


  		




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source(file.path(script_path,function_product_assessment_part0_functions)) #source all functions used in this script 


  		




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##Don't load part 1 and part2, mosaic package does not work on NEX


  		




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#function_product_assessment_part1_functions <- "global_product_assessment_part1_functions_09192016b.R"


  		




  ......




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infile_mask <- args[14]


  		




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in_dir1 <- args[15] #PARAM 15, files containing assessment information


  		




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layers_option <- args[16] # PARAM 17 options are:


  		




  
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tmp_files <- args[17]


  		




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#### values used for testing


  		




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# var <- "TMAX" # variable being interpolated #PARAM 1, arg 1


  		




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# in_dir <- "/nobackupp6/aguzman4/climateLayers/out/reg6/assessment" #PARAM2


  		




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# region_name <- c("reg6") #PARAM 3, arg 3


  		




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# out_suffix <- "predictions_assessment_reg6_10302016" #PARAM 4


  		




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# #out_suffix_str <- region_name #PARAM 4, CONST 3


  		




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# out_dir <- "/nobackupp6/aguzman4/climateLayers/out/reg6/assessment" #PARAM 5


  		




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# create_out_dir_param <- TRUE #PARAM 12, arg 6


  		




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# year_predicted <- c(2000) #PARAM 7, arg7


  		




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# num_cores <- 6 #number of cores used # PARAM 8, arg 8


  		




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# max_mem <- 1e+07 #PARAM 9


  		




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# #mosaicing_method <- args[10] #PARAM10


  		




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# item_no <- 9 #PARAM 10, arg 10


  		




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# metric_name <- "rmse" # "mae", "r" for MAE, R etc.; can also be ns or nv? #PARAM 11, arg 11


  		




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# day_start <- "2000101" #PARAM 12, arg 12


  		




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# day_end <- "20001231" #PARAM 13, arg 13


  		




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# infile_mask <- "/nobackupp8/bparmen1/NEX_data/regions_input_files/r_mask_LST_reg6.tif" #PARAM 14, arg 14


  		




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# in_dir1 <- "/nobackupp6/aguzman4/climateLayers/out" # PARAM 15 On NEX


  		




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# layers_option <- c("var_pred") #PARAM 16, arg 16


  		




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var <- "TMAX" # variable being interpolated #PARAM 1, arg 1


  		




  
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in_dir <- "/nobackupp6/aguzman4/climateLayers/out/reg6/assessment" #PARAM2


  		




  
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region_name <- c("reg6") #PARAM 3, arg 3


  		




  
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out_suffix <- "predictions_assessment_reg6_10302016" #PARAM 4


  		




  
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#out_suffix_str <- region_name #PARAM 4, CONST 3


  		




  
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out_dir <- "/nobackupp6/aguzman4/climateLayers/out/reg6/assessment" #PARAM 5


  		




  
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create_out_dir_param <- TRUE #PARAM 12, arg 6


  		




  
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year_predicted <- c(2000) #PARAM 7, arg7


  		




  
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num_cores <- 6 #number of cores used # PARAM 8, arg 8


  		




  
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max_mem <- 1e+07 #PARAM 9


  		




  
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#mosaicing_method <- args[10] #PARAM10


  		




  
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item_no <- 9 #PARAM 10, arg 10


  		




  
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metric_name <- "rmse" # "mae", "r" for MAE, R etc.; can also be ns or nv? #PARAM 11, arg 11


  		




  
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day_start <- "20000101" #PARAM 12, arg 12


  		




  
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day_end <- "20001231" #PARAM 13, arg 13


  		




  
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infile_mask <- "/nobackupp8/bparmen1/NEX_data/regions_input_files/r_mask_LST_reg6.tif" #PARAM 14, arg 14


  		




  
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in_dir1 <- "/nobackupp6/aguzman4/climateLayers/out" # PARAM 15 On NEX


  		




  
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layers_option <- c("var_pred") #PARAM 16, arg 16


  		




  
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tmp_files <- FALSE #PARAM 17, arg 17


  		




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###################


  		




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### CONSTANT: not set from command line


  		




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#countries_shp <-"/data/project/layers/commons/NEX_data/countries.shp" #Atlas


  		




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countries_shp <- "/nobackupp8/bparmen1/NEX_data/countries.shp" #PARAM 17


  		




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lf_raster <- NULL #list of raster to consider #PARAM 18


  		




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scaling <- 0


  		




  
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scaling <- 1


  		




  
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data_type <- "Int16"


  		




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#CRS_interp <- "+proj=longlat +ellps=WGS84 +datum=WGS84 +towgs84=0,0,0" #param 3


  		




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#list_models<-c("y_var ~ s(lat,lon,k=5) + s(elev_s,k=3) + s(LST,k=3)") #param 4


  		




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  ......




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#parse input value range


  		




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#values_range <- as.numeric(unlist(strsplit(values_range,",")))


  		




  
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#scaling <- 1


  		




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scaling <- as.numeric(scaling)


  		




  
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#data_type <- "Int16"


  		




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#i<-1


  		




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##### prepare list of parameters for call of function


  		




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list_param_predictions_tiles_missing <- list(in_dir1,region_name,y_var_name,interpolation_method,out_suffix,out_dir,


  		




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                                             create_out_dir_param,proj_str,year_predicted,file_format,NA_flag_val,


  		




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                                             num_cores,plotting_figures,item_no,day_to_mosaic_range,countries_shp,plotting_figures,


  		




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                                             #threshold_missing_day,


  		




  
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                                             scaling, data_type, python_bin,tmp_files,


  		




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                                             pred_mod_name,metric_name)


  		




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names(list_param_predictions_tiles_missing) <- c("in_dir1","region_name","y_var_name","interpolation_method","out_suffix","out_dir",


  		




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                                             "create_out_dir_param","proj_str","year_predicted","file_format","NA_flag_val",


  		




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                                             "num_cores","plotting_figures","item_no","day_to_mosaic_range","countries_shp","plotting_figures",


  		




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                                             #"threshold_missing_day",


  		




  
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                                             "scaling", "data_type", "python_bin","tmp_files",


  		




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                                             "pred_mod_name","metric_name")


  		




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#Product assessment


  		




  
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function_product_assessment_part0_functions <- "global_product_assessment_part0_functions_11292016b.R"


  		




  
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source(file.path(script_path,function_product_assessment_part0_functions)) #source all functions used in this script 


  		




  
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#debug(predictions_tiles_missing_fun)


  		




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#Started at 11.06pm


  		




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obj_predictions_tiles_missing_fun <- predictions_tiles_missing_fun(list_param=list_param_predictions_tiles_missing)


  		












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