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Revision 75b5c75d

Added by Benoit Parmentier about 11 years ago

running test with modified code for monthly hold out and gam CAI in OR

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climate/research/oregon/interpolation/master_script_temp.R
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#STAGE 5: Output analyses: assessment of results for specific dates...
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#
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#AUTHOR: Benoit Parmentier                                                                       
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#DATE: 08/31/2013                                                                                 
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#DATE: 09/01/2013                                                                                 
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#PROJECT: NCEAS INPLANT: Environment and Organisms --TASK#363, TASK$568--   
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......
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#source(file.path(script_path,"download_and_produce_MODIS_LST_climatology_06112013.R"))
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source(file.path(script_path,"covariates_production_temperatures_08052013.R"))
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source(file.path(script_path,"Database_stations_covariates_processing_function_06112013.R"))
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source(file.path(script_path,"GAM_fusion_analysis_raster_prediction_multisampling_08302013.R"))
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source(file.path(script_path,"GAM_fusion_analysis_raster_prediction_multisampling_09012013.R"))
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source(file.path(script_path,"results_interpolation_date_output_analyses_08052013.R"))
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#source(file.path(script_path,"results_covariates_database_stations_output_analyses_04012013.R")) #to be completed
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......
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#met_stations_outfiles_obj_file<-"met_stations_outfiles_obj_gam_CAI__365d_gam_CAI_lst_comb3_08252013.RData"
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var<-"TMAX" # variable being interpolated
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out_prefix<-"_365d_gam_CAI_lst_comb3_08312013"                #User defined output prefix
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out_suffix<-"_OR_08312013"                                       #Regional suffix
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out_prefix<-"_365d_gam_CAI_lst_comb3_09012013"                #User defined output prefix
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out_suffix<-"_OR_09012013"                                       #Regional suffix
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out_suffix_modis <-"_05302013"                       #pattern to find tiles produced previously     
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#interpolation_method<-c("gam_fusion","gam_CAI","gam_daily") #other otpions to be added later
......
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nb_sample_month <-1           #number of time random sampling must be repeated for every hold out proportion
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step_month <-0.1         
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constant_month <-0             #if value 1 then use the same samples as date one for the all set of dates
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prop_minmax_month <-c(0,0.1)  #if prop_min=prop_max and step=0 then predictions are done for the number of dates...
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prop_minmax_month <-c(0.2,0.3)  #if prop_min=prop_max and step=0 then predictions are done for the number of dates...
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#dates_selected<-c("20100101","20100102","20100103","20100901") # Note that the dates set must have a specific format: yyymmdd
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#dates_selected<-c("20100101","20100102","20100301","20100302","20100501","20100502","20100701","20100702","20100901","20100902","20101101","20101102")

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