Revision 43a74df2
Added by Benoit Parmentier about 9 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: 10/23/2015
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#MODIFIED ON: 10/26/2015
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#Version: 5 |
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#PROJECT: Environmental Layers project |
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#COMMENTS: analyses run for reg4 1992 for test of mosaicing using 1500x4500km and other tiles |
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infile_mask <- "/data/project/layers/commons/NEX_data/output_run10_1500x4500_global_analyses_pred_1992_10052015/r_mask_reg4.tif" |
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#tb_accuracy_name <- file.path(in_dir,paste("tb_diagnostic_v_NA","_",out_suffix_str,".txt",sep=""))
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tb_accuracy_name <- "/data/project/layers/commons/NEX_data/output_run10_1500x4500_global_analyses_pred_1992_10052015/tb_diagnostic_v_NA_run10_1500x4500_global_analyses_pred_1992_10052015.txt" |
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########################## START SCRIPT ############################## |
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setwd(out_dir) |
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tb <- read.table(file=file.path(in_dir,paste("tb_diagnostic_v_NA","_",out_suffix_str,".txt",sep="")),sep=",")
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lf_mosaic1 <-list.files(path=file.path(in_dir_tiles), |
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pattern=paste(".*.",day_to_mosaic[1],".*.tif$",sep=""),full.names=T) #choosing date 2...20100901
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lf_mosaic2 <-list.files(path=file.path(in_dir_tiles), |
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pattern=paste(".*.",day_to_mosaic[2],".*.tif$",sep=""),full.names=T) #choosing date 2...20100901
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tb <- read.table(file=tb_accuracy_name,sep=",") |
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#list all files to mosaic for a list of day |
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lf_mosaic <- lapply(1:length(day_to_mosaic),FUN=function(i){list.files(path=file.path(in_dir_tiles),
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pattern=paste(".*.",day_to_mosaic[i],".*.tif$",sep=""),full.names=T)})
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##################### PART 2: produce the mosaic ################## |
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########################## |
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#### First generate rmse images for each date and tile for the region |
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lf <- lf_mosaic1 #list of files to mosaic for date 1, there a 28 files for reg4, South America |
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#lf <- lf_mosaic1 #list of files to mosaic for date 1, there a 28 files for reg4, South America |
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lf <- lf_mosaic #list of files to mosaic for date 1, there a 28 files for reg4, South America |
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#tb <- list_param$tb #fitting or validation table with all days |
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#metric_name <- "rmse" #RMSE, MAE etc. |
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out_dir_str <- out_dir |
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out_suffix_str <- out_suffix |
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#Improve by adding multicores option |
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list_param_accuracy_metric_raster <- list(lf,tb,metric_name,pred_mod_name,y_var_name,interpolation_method, |
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days_to_process,NA_flag_val,file_format,out_dir_str,out_suffix_str) |
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names(list_param_accuracy_metric_raster) <- c("lf","tb","metric_name","pred_mod_name","y_var_name","interpolation_method",
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"days_to_process","NA_flag_val","file_format","out_dir_str","out_suffix_str") |
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list_raster_created_obj <- lapply(1:length(day_to_mosaic),FUN=create_accuracy_metric_raster, |
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list_param=list_param_accuracy_metric_raster) |
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#debug(create_accuracy_metric_raster) |
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raster_created_obj <- create_accuracy_metric_raster(1, list_param_accuracy_metric_raster) |
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#list_raster_created_obj <- lapply(1:1,FUN=create_accuracy_metric_raster, |
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# list_param=list_param_accuracy_metric_raster) |
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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 <- unlist(raster_created_obj$list_raster_name)
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lf_accuracy_raster <- lapply(1:length(list_raster_created_obj),FUN=function(i){unlist(list_raster_created_obj[[i]]$list_raster_name)})
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#Plot as quick check |
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r1 <- raster(lf_mosaic1[1])
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r1 <- raster(lf_mosaic[[1]][1])
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#r2 <- raster(lf_mosaic2[2]) |
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plot(r1) |
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#plot(r2) |
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r1_ac <- raster(lf_accuracy_raster[1]) |
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r1_ac <- raster(lf_accuracy_raster[[1]][1])
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plot(r1_ac) |
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################################# |
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#### Second mosaic tiles for the variable and accuracy metrid |
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#methods availbable:use_sine_weights,use_edge,use_linear_weights |
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#only use edge method for now |
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#loop to dates..., make this a function... |
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for(i in 1:length(day_to_mosaic)){
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mosaic_method <- "use_edge_weights" #this is distance from edge |
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out_suffix_str <- paste(interpolation_method,y_var_name,day_to_mosaic[i],out_suffix,sep="_")
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out_suffix_tmp <- paste(interpolation_method,y_var_name,day_to_mosaic[i],out_suffix,sep="_")
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#debug(mosaicFiles) |
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#can also loop through methods!!! |
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python_bin <- "/usr/bin/" #python gdal bin, this may change on NEX! |
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mosaic_edge_obj_prediction <- mosaicFiles(lf_mosaic1,
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mosaic_edge_obj_prediction <- mosaicFiles(lf_mosaic[[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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df_points=NULL,NA_flag=NA_flag_val, |
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file_format=file_format,out_suffix=out_suffix_str,
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file_format=file_format,out_suffix=out_suffix_tmp,
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out_dir=out_dir) |
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mosaic_method <- "use_edge_weights" #this is distance from edge |
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out_suffix_str <- paste(interpolation_method,metric_name,day_to_mosaic[i],out_suffix,sep="_")
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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 also loop through methods!!! |
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mosaic_edge_obj_accuracy <- mosaicFiles(lf_accuracy_raster, |
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mosaic_edge_obj_accuracy <- mosaicFiles(lf_accuracy_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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df_points=NULL,NA_flag=NA_flag_val, |
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file_format=file_format,out_suffix=out_suffix_str,
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file_format=file_format,out_suffix=out_suffix_tmp,
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out_dir=out_dir) |
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list_mosaic_obj[[i]] <- list(prediction=mosaic_edge_obj_prediction,accuracy=mosaic_edge_obj_accuracy) |
Also available in: Unified diff
testing mask and python path on Atlas