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Revision 96cf6457

Added by Benoit Parmentier over 8 years ago

more testing of stage 7 with observation maps of n

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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: 08/16/2016
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#MODIFIED ON: 08/22/2016
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#PROJECT: NCEAS INPLANT: Environment and Organisms                                                                           
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#First source these files:
......
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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_08222016.R"
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#function_mosaicing_functions <- "global_run_scalingup_mosaicing_function_07052016.R" #PARAM12
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function_mosaicing <-"global_run_scalingup_mosaicing_08162016.R"
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function_mosaicing <-"global_run_scalingup_mosaicing_08222016.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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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 <- "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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#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("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 <- 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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scaling <- 1 #use this if predicting n rather than other variables
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#values_range <- "-100,100"
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values_range <- "0,32767" #this is for n variable
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NA_flag_val <- -32768 #should be here
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