Revision b0b0ba02
Added by Benoit Parmentier almost 11 years ago
| climate/research/oregon/interpolation/multi_timescales_paper_interpolation_functions.R | ||
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# interpolation code. |
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#Functions used in the production of figures and data for the multi timescale paper are recorded. |
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#AUTHOR: Benoit Parmentier # |
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#DATE: 11/25/2013 |
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#DATE CREATED: 11/25/2013 |
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#DATE MODIFIED: 12/04/2013 |
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#Version: 1 |
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#PROJECT: Environmental Layers project # |
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################################################################################################# |
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#### FUNCTION USED IN SCRIPT |
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function_analyses_paper <-"multi_timescales_paper_interpolation_functions_11252013.R"
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function_analyses_paper <-"multi_timescales_paper_interpolation_functions_11022013.R"
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plot_transect_m2<-function(list_trans,r_stack,title_plot,disp=FALSE,m_layers){
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#This function creates plot of transects for stack of raster images. |
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return(list_trans_data) |
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} |
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### Need to improve this function!!! |
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calc_stat_prop_tb_diagnostic <-function(names_mod,names_id,tb){
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t<-melt(subset(tb,pred_mod==names_mod), |
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measure=c("mae","rmse","r","me","m50"),
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id=names_id, |
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na.rm=T) |
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char_tmp <-rep("+",length=length(names_id)-1)
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var_summary <-paste(names_id,sep="",collapse=char_tmp) |
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var_summary_formula <-paste(var_summary,collpase="~variable") |
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avg_tb<-cast(t,var_summary_formula,mean) |
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sd_tb<-cast(t,var_summary_formula,sd) |
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n_tb<-cast(t,var_summary_formula,length) |
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#n_NA<-cast(t,dst_cat1~variable,is.na) |
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#### prepare returning object |
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prop_obj<-list(tb,avg_tb,sd_tb,n_tb) |
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names(prop_obj) <-c("tb","avg_tb","sd_tb","n_tb")
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return(prop_obj) |
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} |
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#Calculate the difference between training and testing in two different data.frames. Columns to substract are provided. |
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diff_df<-function(tb_s,tb_v,list_metric_names){
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tb_diff<-vector("list", length(list_metric_names))
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for (i in 1:length(list_metric_names)){
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metric_name<-list_metric_names[i] |
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tb_diff[[i]] <-tb_s[,c(metric_name)] - tb_v[,c(metric_name)] |
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} |
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names(tb_diff)<-list_metric_names |
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tb_diff<-as.data.frame(do.call(cbind,tb_diff)) |
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return(tb_diff) |
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} |
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### generate filter for Moran's I function in raster package |
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autocor_filter_fun <-function(no_lag=1,f_type="queen"){
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Also available in: Unified diff
multi timescale function script, small update