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Revision b0b0ba02

Added by Benoit Parmentier about 11 years ago

multi timescale function script, small update

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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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