Revision b695b5f1
Added by Benoit Parmentier about 8 years ago
| 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: 11/16/2016
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#MODIFIED ON: 11/20/2016
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#Version: 1 |
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#PROJECT: Environmental Layers project |
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#COMMENTS: |
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#source /nobackupp6/aguzman4/climateLayers/sharedModules2/etc/environ.sh |
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# |
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#setfacl -Rm u:aguzman4:rwx /nobackupp6/aguzman4/climateLayers/LST_tempSpline/ |
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#COMMIT: testing and moving generate raster of number of predictions for day with missing tiles
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#COMMIT: debugging function of number of predictions for day with missing tiles
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################################################################################################# |
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############################### |
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####### Parameters, constants and arguments ### |
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CRS_locs_WGS84<-CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +towgs84=0,0,0") #constant 1
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#CRS_locs_WGS84 <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +towgs84=0,0,0") #constant 1
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proj_str <- "+proj=longlat +ellps=WGS84 +datum=WGS84 +towgs84=0,0,0" |
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var<-"TMAX" # variable being interpolated #param 1, arg 1 |
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interpolation_method<-c("gam_CAI") #param 2
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CRS_interp <- "+proj=longlat +ellps=WGS84 +datum=WGS84 +towgs84=0,0,0" #param 3 |
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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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metric_name <- "var_pred" #use RMSE if accuracy |
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pred_mod_name <- "mod1" |
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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,list_year_predicted,file_format,NA_flag_val, |
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num_cores,plotting_figures,item_no,day_to_mosaic,countries_shp,plot_region, |
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threshold_missing_day,pred_mod_name,metric_name) |
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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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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","list_year_predicted","file_format","NA_flag_val", |
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"num_cores","plotting_figures","item_no","day_to_mosaic","countries_shp","plot_region", |
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"threshold_missing_day","pred_mod_name","metric_name") |
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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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"pred_mod_name","metric_name") |
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debug(predictions_tiles_missing_fun) |
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predictions_tiles_missing_fun(1,list_param=list_param_predictions_tiles_missing) |
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##for plotting assessment function |
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item_no <- list_param_run_assessment_prediction$mosaic_plot #PARAM14 |
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day_to_mosaic <- list_param$day_to_mosaic #PARAM15
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day_to_mosaic_range <- list_param$day_to_mosaic_range #PARAM15
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countries_shp <- list_param$countries_shp #PARAM17 |
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plot_region <- list_param$plot_region #PARAM18
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threshold_missing_day <- list_param$threshold_missing_day #PARM20 |
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plotting_figures <- list_param$plotting_figures #PARAM18
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#threshold_missing_day <- list_param$threshold_missing_day #PARM20
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pred_mod_name <- list_param$pred_mod_name |
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metric_name <- list_param$metric_name |
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Also available in: Unified diff
debugging function of number of predictions for day with missing tiles