[R] How to save output of multiple unique loops in R.

[Ioanna Ioannou]

Hello everyone,

Could you please let me know how to create a new data.frame with the output of the 2 unique loops. Essentially i want a data.frame with the IM, Taxonomy and VC . MInd you VC is a vector with 33 elements.

Any ideas?

best,
ioanna

D<- data.frame(Ref.No = c(1622, 1623, 1624, 1625, 1626, 1627, 1628, 1629),  Region = rep(c('South America'), times = 8),
               IM.type = c('PGA', 'PGA', 'PGA', 'PGA', 'Sa', 'Sa', 'Sa', 'Sa'),
               Damage.state = c('DS1', 'DS2', 'DS3', 'DS4','DS1', 'DS2', 'DS3', 'DS4'),
               Taxonomy = c('ER+ETR_H1','ER+ETR_H1','ER+ETR_H1','ER+ETR_H1','ER+ETR_H2','ER+ETR_H2','ER+ETR_H2','ER+ETR_H2'),
               Prob.of.exceedance_1 = c(0,0,0,0,0,0,0,0),
               Prob.of.exceedance_2 = c(0,0,0,0,0,0,0,0),
              Prob.of.exceedance_3 =c(0.26,0.001,0.00019,0.000000573,0.04,0.00017,0.000215,0.000472),
              Prob.of.exceedance_4 =
                c(0.72,0.03,0.008,0.000061,0.475,0.0007,0.00435,0.000405),
              stringsAsFactors=FALSE)



# names of the variables used in the calculations
calc_vars<-paste("Prob.of.exceedance",1:4,sep="_")
# get the rows for the four damage states
DS1_rows <-D$Damage.state == "DS1"
DS2_rows <-D$Damage.state == "DS2"
DS3_rows <-D$Damage.state == "DS3"
DS4_rows <-D$Damage.state == "DS4"
# step through all possible values of IM.type and Taxonomy
for(IM in unique(D$IM.type)) {  for(Tax in unique(D$Taxonomy)) {
# get a logical vector of the rows to be used in this calculation
calc_rows <- D$IM.type == IM & D$Taxonomy == Tax
cat(IM,Tax,calc_rows,"\n")
# check that there are any such rows in the data frame
if(sum(calc_rows)) {
  # if so, fill in the four values for these rows
  VC <- 0.0 * (1- D[calc_rows & DS1_rows,calc_vars]) +
    0.02* (D[calc_rows & DS1_rows,calc_vars] -
               D[calc_rows & DS2_rows,calc_vars]) +
    0.10* (D[calc_rows & DS2_rows,calc_vars] -
                                   D[calc_rows & DS3_rows,calc_vars]) +
    0.43 * (D[calc_rows & DS3_rows,calc_vars] -
                                   D[calc_rows & DS4_rows,calc_vars]) +
    1.0*   D[calc_rows & DS4_rows,calc_vars]

}
}
}



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