Revision d7a1ad79
Added by Benoit Parmentier over 8 years ago
| climate/research/oregon/interpolation/master_script_stage_7.R | ||
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#AUTHOR: Benoit Parmentier |
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#CREATED ON: 01/01/2016 |
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#MODIFIED ON: 06/19/2016
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#MODIFIED ON: 06/24/2016
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#PROJECT: NCEAS INPLANT: Environment and Organisms |
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#First source these files: |
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#run mosaic for ac testing, n |
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#Rscript /nobackupp8/bparmen1/env_layers_scripts/master_script_stage_7_06192016.R TMAX /nobackupp6/aguzman4/climateLayers/out/ reg4 reg4_1999 /nobackupp8/bparmen1/climateLayers/out/reg4 TRUE 1999 6 1e+07 use_edge_weights n 19990107 19990108 /nobackupp8/bparmen1/NEX_data/regions_input_files/r_mask_LST_reg4.tif /nobackupp6/aguzman4/climateLayers/out/reg4/assessment/output_reg4_1999/df_assessment_files_reg4_1999_reg4_1999.txt python ac_testing FALSE Int16 100 -100,100 |
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#Rscript /nobackupp8/bparmen1/env_layers_scripts/master_script_stage_7_06192016.R TMAX /nobackupp6/aguzman4/climateLayers/out/ reg5 reg5_1985 /nobackupp6/aguzman4/climateLayers/out/reg5/mosaicsAc/ TRUE 1981 6 1e+07 use_edge_weights n 19910101 19910101 /nobackupp8/bparmen1/NEX_data/regions_input_files/r_mask_LST_reg5.tif /nobackupp6/aguzman4/climateLayers/out/reg5/assessment/output_reg5_1985/df_assessment_files_reg5_1985_reg5_1985.txt python ac_testing FALSE Int16 100 -100,100 |
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#script /nobackupp8/bparmen1/env_layers_scripts/master_script_stage_7_06192016.R TMAX /nobackupp6/aguzman4/climateLayers/out/ reg5 reg5_1985 /nobackupp6/aguzman4/climateLayers/out/reg5/mosaicsAc/ TRUE 1985 6 1e+07 use_edge_weights n 19850101 19850101 /nobackupp8/bparmen1/NEX_data/regions_input_files/r_mask_LST_reg5.tif /nobackupp6/aguzman4/climateLayers/out/reg5/assessment/output_reg5_1985/df_assessment_files_reg5_1985_reg5_1985.txt python ac_testing FALSE Int16 100 -100,100 |
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################################################################################################## |
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### PARAMETERS DEFINED IN THE SCRIPT |
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#script_path <- "/home/parmentier/Data/IPLANT_project/env_layers_scripts" |
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script_path <- "/nobackupp8/bparmen1/env_layers_scripts" #path to script |
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function_mosaicing_functions <- "global_run_scalingup_mosaicing_function_06192016.R" #PARAM12
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function_mosaicing <-"global_run_scalingup_mosaicing_06192016.R"
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function_mosaicing_functions <- "global_run_scalingup_mosaicing_function_07012016.R" #PARAM12
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function_mosaicing <-"global_run_scalingup_mosaicing_07012016.R"
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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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#The 20 arguments are passed directly from Rscript: |
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### Use the following values to run code from the shell: |
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# var <- "TMAX" # variable being interpolated #param 1, arg 1
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# in_dir <- "/nobackupp6/aguzman4/climateLayers/out/" #PARAM2,arg 2
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# region_name <- "reg4" #PARAM 3, arg 3 #reg4 South America, Africa reg5,Europe reg2, North America reg1, Asia reg3
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# out_suffix <- "reg4_1999" #PARAM 4, arg 4
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# out_suffix_str <- region_name #PARAM 4, CONST 3
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# out_dir <- "/nobackupp8/bparmen1/climateLayers/out/reg4" #PARAM 5,arg 5 use this location for now
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# create_out_dir_param <- TRUE #PARAM 6, arg 6
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# year_predicted <- 1999 #PARAM 7, arg 7
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# num_cores <- 6 #PARAM 8, arg 8
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# max_mem = 1e+07 #param 9, arg 9
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# mosaicing_method <- "use_edge_weights" #PARAM10, 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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var <- "TMAX" # variable being interpolated #param 1, arg 1 |
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in_dir <- "/nobackupp6/aguzman4/climateLayers/out/" #PARAM2,arg 2 |
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region_name <- "reg5" #PARAM 3, arg 3 #reg4 South America, Africa reg5,Europe reg2, North America reg1, Asia reg3
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out_suffix <- "reg5_1991" #PARAM 4, arg 4
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out_suffix_str <- region_name #PARAM 4, CONST 3 |
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out_dir <- "/nobackupp8/bparmen1/climateLayers/out/reg5/mosaicsAc" #PARAM 5,arg 5 use this location for now
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create_out_dir_param <- TRUE #PARAM 6, arg 6 |
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year_predicted <- 1991 #PARAM 7, arg 7
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num_cores <- 6 #PARAM 8, arg 8
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max_mem = 1e+07 #param 9, arg 9 |
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mosaicing_method <- "use_edge_weights" #PARAM10, 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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#metric_name <- "n" |
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#metric_name <- "mae" |
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#day_start <- "19990701" #PARAM 12 arg 12 |
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#day_end <- "19990703" #PARAM 13 arg 13 |
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#day_start <- "19990107" #PARAM 12 arg 12 |
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#day_end <- "19990108" #PARAM 13 arg 13 |
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#infile_mask <- "/nobackupp8/bparmen1/NEX_data/regions_input_files/r_mask_LST_reg4.tif" #PARAM 14, arg 14 |
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#df_assessment_files_name <- "/nobackupp6/aguzman4/climateLayers/out/reg4/assessment/output_reg4_1999/df_assessment_files_reg4_1999_reg4_1999.txt" # data.frame with all files used in assessmnet, PARAM 15 |
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#algorithm <- "python" #PARAM 16 #if R use mosaic function for R, if python use modified gdalmerge script from Alberto Guzmann |
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day_start <- "19910101" #PARAM 12 arg 12 |
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day_end <- "19910101" #PARAM 13 arg 13 |
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infile_mask <- "/nobackupp8/bparmen1/NEX_data/regions_input_files/r_mask_LST_reg5.tif" #PARAM 14, arg 14 |
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df_assessment_files_name <- "/nobackupp6/aguzman4/climateLayers/out/reg5/assessment/output_reg5_1991/df_assessment_files_reg5_1991_reg5_1991.txt" # data.frame with all files used in assessmnet, PARAM 15 |
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#df_assessment_files_name <- "/nobackupp6/aguzman4/climateLayers/out/reg5/assessment/output_reg5_1985/df_assessment_files_reg5_1985_reg5_1985.txt" |
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algorithm <- "python" #PARAM 16 #if R use mosaic function for R, if python use modified gdalmerge script from Alberto Guzmann |
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#layers_option <- c("var_pred") #arg 17 ,param 17, options are:#res_training, res_testing,ac_training, ac_testing, var_pred
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#layers_option <- c("ac_training") #arg 17 ,param 17, options are:#res_training, res_testing,ac_training, ac_testing, var_pred
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#layers_option <- c("res_training") # #arg 17 ,param 17, options are:#res_training, res_testing,ac_training, ac_testing, var_pred
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#layers_option <- c("res_testing") #arg 17 ,param 17, options are:#res_training, res_testing,ac_training, ac_testing, var_pred
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#layers_option <- c("ac_testing") #arg 17 ,param 17, options are:#res_training, res_testing,ac_training, ac_testing, var_pred
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layers_option <- c("ac_testing") #arg 17 ,param 17, options are:#res_training, res_testing,ac_training, ac_testing, var_pred
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#tmp_files <- TRUE #arg 18, param 18, keep temp files if TRUE
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#data_type <- "Int16" #, param 19, use int32 for output layers mosaiced
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#scaling <- 100 #, param 20, if null use 1
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#values_range <- "-100,100"
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#NA_flag_val <- -32768 #should be here
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tmp_files <- FALSE #arg 18, param 18, keep temp files if TRUE
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data_type <- "Int16" #, param 19, use int32 for output layers mosaiced |
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scaling <- 100 #, param 20, if null use 1 |
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values_range <- "-100,100" |
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NA_flag_val <- -32768 #should be here |
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#path_assessment <- NOT USED "/nobackupp6/aguzman4/climateLayers/out/reg4/assessment/output_reg4_1991" #PARAM 14a, arg 14 |
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#debug(debug_fun_test) |
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#debug_fun_test(list_param_raster_prediction) |
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i <- 1 #this select the first year of list_year_predicted |
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#function_mosaicing_functions <- "global_run_scalingup_mosaicing_function_05312016.R" #PARAM12
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#function_mosaicing <-"global_run_scalingup_mosaicing_06072016.R"
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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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function_mosaicing_functions <- "global_run_scalingup_mosaicing_function_06232016.R" #PARAM12
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function_mosaicing <-"global_run_scalingup_mosaicing_06232016.R"
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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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if (stages_to_run[7]==7){
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assessment_prediction_obj <- run_mosaicing_prediction_fun(i,list_param_run_mosaicing_prediction) |
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