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Revision 0cdba0f3

Added by Benoit Parmentier over 8 years ago

master script mosaicing debugging of accuracy layers

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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: 05/30/2016  
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#MODIFIED ON: 05/31/2016  
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#PROJECT: NCEAS INPLANT: Environment and Organisms                                                                           
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#First source these files:
......
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#source /nobackupp6/aguzman4/climateLayers/sharedModules2/etc/environ.sh  
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#MODULEPATH=$MODULEPATH:/nex/modules/files
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#module load pythonkits/gdal_1.10.0_python_2.7.3_nex
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#Set permissions:
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#setfacl -Rm u:aguzman4:rwx /nobackupp6/aguzman4/climateLayers/LST_tempSpline/
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#
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## TODO:
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# 
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## Comments: dealing with flags and datatype in output mosaics
......
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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_05302016.R" #PARAM12
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function_mosaicing <-"global_run_scalingup_mosaicing_05302016.R"
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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_05312016.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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......
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metric_name <- "rmse" #RMSE, MAE etc. #PARAM 11, arg 11
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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 <- "19990109" #PARAM 12 arg 12
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day_end <- "19990111" #PARAM 13 arg 13
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day_start <- "19990108" #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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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_testing") #arg 17 ,param 17, options are:#res_training, res_testing,ac_training, ac_testing, var_pred
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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_testing") #arg 17 ,param 17, options are:#res_training, res_testing,ac_training, ac_testing, var_pred
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tmp_files <- FALSE #arg 18, param 18, keep temp files if TRUE
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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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#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_05302016.R" #PARAM12
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function_mosaicing <-"global_run_scalingup_mosaicing_05302016.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_05312016.R" #PARAM12
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#function_mosaicing <-"global_run_scalingup_mosaicing_05312016.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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