Revision 8d184742
Added by Benoit Parmentier over 8 years ago
| climate/research/oregon/interpolation/global_run_scalingup_mosaicing.R | ||
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#Analyses, figures, tables and data are also produced in the script. |
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#AUTHOR: Benoit Parmentier |
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#CREATED ON: 04/14/2015 |
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#MODIFIED ON: 05/01/2016
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#MODIFIED ON: 05/31/2016
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#Version: 6 |
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#PROJECT: Environmental Layers project |
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#COMMENTS: analyses run for reg4 1991 for test of mosaicing using 1500x4500km and other tiles |
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### Read in assessment and accuracy files |
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df_assessment_files <- read.table(df_assessment_files_name,stringsAsFactors=F,sep=",") |
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#browser() |
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tb_v_accuracy_name <- df_assessment_files$files[2] |
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tb_s_accuracy_name <- df_assessment_files$files[4] |
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tb_s_month_accuracy_name <- df_assessment_files$files[3] |
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#this part needs to be improve make this a function and use multicore to loop through files... |
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#give a range of dates to run... |
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#browser() |
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if(is.null(day_to_mosaic_range)){
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# start_date <- #first date |
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#raster_created_obj <- create_accuracy_metric_raster(1, list_param_accuracy_metric_raster) |
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#Extract list of files for rmse and date 1 (19920101), there should be 28 raster images |
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lf_accuracy_raster <- lapply(1:length(list_raster_created_obj),FUN=function(i){unlist(list_raster_created_obj[[i]]$list_raster_name)})
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lf_accuracy_testing_raster <- lapply(1:length(list_raster_created_obj),FUN=function(i){unlist(list_raster_created_obj[[i]]$list_raster_name)})
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#Plot as quick check |
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#r1 <- raster(lf_mosaic[[1]][1]) |
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} |
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#### Add option for ac training here |
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#################################### |
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###Depending on value of layers_option, create accuracy surfaces based on testing residuals... |
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#browser() |
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if(layers_option=="res_testing"){
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#This part took 19 minutes and 45 seconds |
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#loop to dates..., make this a function... |
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#This is a loop but uses multicores when calling the mosaic function |
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list_mosaic_obj <- vector("list",length=length(day_to_mosaic))
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#browser() |
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for(i in 1:length(day_to_mosaic)){
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# |
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#runs in 15-16 minutes for 3 dates and mosaicing of 28 tiles... |
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list_mosaic_obj[[i]] <- mosaic_obj |
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} |
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#browser() |
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if(layers_option=="ac_testing"){
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## Now accuracy based on center of centroids |
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mosaic_method <- "use_edge_weights" #this is distance from edge |
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#Adding metric name in the name... |
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out_suffix_tmp <- paste(interpolation_method,metric_name,day_to_mosaic[i],out_suffix,sep="_") |
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#debug(mosaicFiles) |
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#Can modify here....add creation of data for the specific date here rather than beforehand!!!! |
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## To be inserted... |
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#undebug(mosaicFiles) |
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#can also loop through methods!!! |
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mosaic_obj <- mosaicFiles(lf_accuracy_raster[[i]], |
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#browser() |
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mosaic_obj <- mosaicFiles(lf_accuracy_testing_raster[[i]], |
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mosaic_method="use_edge_weights", |
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num_cores=num_cores, |
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r_mask_raster_name=infile_mask, |
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python_bin=python_bin, |
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mosaic_python=mosaic_python, |
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algorithm=algorithm, |
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match_extent = match_extent, |
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df_points=NULL, |
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NA_flag=NA_flag_val, |
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file_format=file_format, |
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list_mosaic_obj[[i]] <- mosaic_obj |
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} |
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if(layers_option=="ac_training"){
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## Now accuracy based on center of centroids |
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mosaic_method <- "use_edge_weights" #this is distance from edge |
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#Adding metric name in the name... |
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out_suffix_tmp <- paste(interpolation_method,metric_name,day_to_mosaic[i],out_suffix,sep="_") |
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#Can modify here....add creation of data for the specific date here rather than beforehand!!!! |
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## To be inserted... |
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#undebug(mosaicFiles) |
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#can also loop through methods!!! |
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#browser() |
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mosaic_obj <- mosaicFiles(lf_accuracy_training_raster[[i]], |
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mosaic_method="use_edge_weights", |
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num_cores=num_cores, |
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r_mask_raster_name=infile_mask, |
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python_bin=python_bin, |
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mosaic_python=mosaic_python, |
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algorithm=algorithm, |
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match_extent = match_extent, |
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df_points=NULL, |
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NA_flag=NA_flag_val, |
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file_format=file_format, |
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out_suffix=out_suffix_tmp, |
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out_dir=out_dir, |
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tmp_files=tmp_files, |
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data_type=data_type, |
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scaling=scaling, |
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values_range=values_range) |
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##Took 29 minutes for 28 tiles and one date...!!! |
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list_mosaic_obj[[i]] <- mosaic_obj |
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} |
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#list_mosaic_obj[[i]] <- list(prediction=mosaic_edge_obj_prediction,accuracy=mosaic_edge_obj_accuracy) |
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### produce residuals mosaics |
Also available in: Unified diff
debugging errors in accuracy layers and adding accuracy based on training data