Revision c8cfad3e
Added by Benoit Parmentier over 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: 05/27/2015
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#MODIFIED ON: 06/03/2015
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#Version: 4 |
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#PROJECT: Environmental Layers project |
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#COMMENTS: analyses for run 10 global analyses,all regions 1500x4500km and other tiles |
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y_var_name <- "dailyTmax" #PARAM1 |
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interpolation_method <- c("gam_CAI") #PARAM2
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out_suffix <- "mosaic_run10_1500x4500_global_analyses_05272015" #PARAM3
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out_suffix <- "mosaic_run10_1500x4500_global_analyses_06032015" #PARAM3
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out_dir <- in_dir #PARAM4 |
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create_out_dir_param <- TRUE #PARAM 5 |
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tile_size <- "1500x4500" #PARAM 11 |
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mulitple_region <- TRUE #PARAM 12 |
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region_name <- "reg1" #PARAM 13 #reg1 is North America
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region_name <- "reg5" #PARAM 13 #reg1 is North America, Africa Region 5
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plot_region <- FALSE |
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########################## START SCRIPT ############################## |
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setwd(out_dir) |
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lf_mosaic <-list.files(path=file.path(in_dir), |
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pattern=paste(".*.",day_to_mosaic[2],".*.tif$",sep=""),full.names=T) #choosing date 2...20100901
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lf_mosaic <- lf_mosaic[1:20] |
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r1 <- raster(lf_mosaic[1]) |
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r2 <- raster(lf_mosaic[2]) |
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## Create raster image for original predicted images with matching resolution and extent to the mosaic (reference image) |
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rast_ref <- file.path(out_dir,"avg.tif") #this is a the ref |
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r_ref <- raster(rast_ref) |
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plot(r_ref) |
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### First match weights from linear option |
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lf_files <- unlist(list_linear_r_weights) |
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num_cores <-11 |
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list_linear_weights_prod_m <- mclapply(1:length(lf_files),FUN=raster_match,list_param=list_param_raster_match,mc.preschedule=FALSE,mc.cores = num_cores) |
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### Second match wegihts from sine option |
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lf_files <- unlist(list_sine_r_weights) |
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r_diff_mean_linear <- r_m_mean - r_m_linear_weighted_mean |
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r_diff_mean_sine <- r_m_mean - r_m_sine_weighted_mean |
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r_m_mean_terrain <- terrain(r_m_mean,opt=c("slope","aspect"),unit="degrees")
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r_m_sine_weighted_mean_terrain <- terrain(r_m_sine_weighted_mean,opt=c("slope","aspect"),unit="degrees")
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r_m_linear_weighted_mean_terrain <- terrain(r_m_linear_weighted_mean,opt=c("slope","aspect"),unit="degrees")
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##################### |
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###### PART 5: Now plot of the weighted mean and unweighted mean with the mosaic function ##### |
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dev.off() |
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#### plot terrain to emphasize possible edges.. |
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res_pix <- 1200 |
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col_mfrow <- 1 |
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row_mfrow <- 0.8 |
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png(filename=paste("Figure2_slope_mean_linear_for_region_",region_name,"_",out_suffix,".png",sep=""),
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width=col_mfrow*res_pix,height=row_mfrow*res_pix) |
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plot(r_m_linear_weighted_mean_terrain,y=1) |
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dev.off() |
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png(filename=paste("Figure2_aspect_mean_linear_for_region_",region_name,"_",out_suffix,".png",sep=""),
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width=col_mfrow*res_pix,height=row_mfrow*res_pix) |
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plot(r_m_linear_weighted_mean_terrain,y=2) |
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dev.off() |
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png(filename=paste("Figure2_slope_mean_sine_for_region_",region_name,"_",out_suffix,".png",sep=""),
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width=col_mfrow*res_pix,height=row_mfrow*res_pix) |
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plot(r_m_sine_weighted_mean_terrain,y=1) |
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dev.off() |
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png(filename=paste("Figure2_aspect_mean_sine_for_region_",region_name,"_",out_suffix,".png",sep=""),
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width=col_mfrow*res_pix,height=row_mfrow*res_pix) |
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plot(r_m_sine_weighted_mean_terrain,y=2) |
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dev.off() |
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png(filename=paste("Figure2_slope_mean_for_region_",region_name,"_",out_suffix,".png",sep=""),
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width=col_mfrow*res_pix,height=row_mfrow*res_pix) |
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plot(r_m_mean_terrain,y=1) |
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dev.off() |
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png(filename=paste("Figure2_aspect_mean_for_region_",region_name,"_",out_suffix,".png",sep=""),
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width=col_mfrow*res_pix,height=row_mfrow*res_pix) |
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plot(r_m_mean_terrain,y=2) |
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dev.off() |
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##################### END OF SCRIPT ###################### |
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################################################# |
Also available in: Unified diff
mosaicing test region 1, North America adding figures for two methods